Alvin C. G. VARQUEZ 교수

Abstract Air temperature trends (1960–2009) based on stations in cities, minus those based on global surface temperature datasets, are defined herein as urban heat island (UHI) trends. Urban climate was examined globally by comparing UHI trends with indices of geophysical factors, including background climate, latitude, and diurnal temperature range (DTR) and indices of artificial factors, including anthropogenic heat emission (AHE) and population indices. Surprisingly, a better relationship was

Numerical weather prediction models are progressively used to downscale future climate in cities at increasing spatial resolutions. Boundary conditions representing rapidly growing urban areas are imperative to more plausible future predictions. In this work, 1-km global anthropogenic heat emission (AHE) datasets of the present and future are constructed. To improve present AHE maps, 30 arc-second VIIRS satellite imagery outputs such as nighttime lights and night-fires were incorporated along wi

Urban dwellers are at risk of heat-related mortality in the onset of climate change. In this study, future changes in heat-related mortality of elderly citizens were estimated while considering the combined effects of spatially-varying megacity's population growth, urbanization, and climate change. The target area is the Jakarta metropolitan area of Indonesia, a rapidly developing tropical country. 1.2 × 1.2 km² daily maximum temperatures were acquired from weather model outputs for t

Despite increasing utilization and accuracy of models to predict the future climate and hydrology at higher resolutions, urban areas are still underrepresented. A method to determining future distribution of urban parameters in accordance with the global climate and socio-ecoonomic pathways of the future is proposed. An urban growth model was used to project the expansion of urban areas in 2050 of Jakarta. From shared socio-economic pathways (SSP), total population in the future was acquired. Us

Increasing population in urban areas drives urban cover expansion and spatial growth. Developing urban growth models enables better understanding and planning of sustainable urban areas. The SLEUTH model is an urban growth simulation model which uses the concept of cellular automata to predict land cover change using six spatial inputs of historical data (slope, land use, exclusion, urban, transportation, and hill-shade). This study investigates the potential of SLEUTH to capture railway-induced

Numerical weather prediction models have been improved to adequately represent the growing influence of urban areas to surrounding weather. Recently, updated LES-derived empirical equations on the aero-dynamic urban surface parameters displacement height d, and roughness length for momentum z0m, have been introduced. Using a high spatial resolution d, z0m, and anthropogenic heat emission distribution, dry case simulation was conducted using Weather Research and Forecasting Model with domains cov

The contribution of anthropogenic heat (AH) to the surface energy budget is well known. However, further investigation of realistic AH emissions in cities and their interactions with its surrounding atmospheric environment is still limited. Furthermore, past studies are site-specific providing limited insight to general impacts of AH. In this study, a realistic, high-spatiotemporal AHE dataset was used as surface boundary input into a weather model. With monthly-representative typical diurnal cl

A systematic method to project the future distribution of population in megacities is introduced. Two general steps were discussed: (1) estimation of urban sprawl by an urban growth model, SLEUTH; (2) estimation of population distribution by a logistic model with variable empirical coefficients. Predicting the annual change from 2014 to 2050, Jakarta megacity was used as a benchmark urban agglomeration. The key inputs are historical land cover and geographic information, transportation networks,

Spatiotemporal evaluation of human mobility is crucial to deepen and broaden the understanding of drivers and mechanisms behind urbanization. In this study, daytime human mobility was quantified based on the inflow and outflow of population in 500 × 500 m spatial grids using a processed version of the hourly DOCOMO Mobile Spatial Statistics (MSS) dataset. Using K-means clustering of the temporal mobility values over the Greater Tokyo Area, five typical diurnal patterns representing distinguishab

The evaluation of thermal comfort in urban outdoor spaces has become increasingly important due to growing concerns about climate change and heat island effects. Many thermal comfort indices have been developed, but existing indices, such as the SET, assume steady-state conditions. Hence, it may not adequately capture outdoor thermal comfort in the short-term, especially under rapidly changing thermal environments (e.g., walking from indoors to outdoors). To address these limitations, this study

AH4GUC is a database which contains maps of hourly-representative anthropogenic heat emissions (AHE) representing the periods 2010s and 2050s. The AHE of 2050s represents a single future scenario based on RCP8.5 and SSP3 climate change pathways. This future “business-as-usual” scenario assumes minimal or no adaptation and mitigation measures implemented in all countries. Monthly-averaged and annual-averaged values representing the 2010s and 2050s are also provided. All files are available in sin